Staff Technical Program Manager, SOX Compliance

What you’ll do:

• Lead strategic compliance engineering programs that span multiple teams and organizations, translating broad risk and control objectives into executable roadmaps, milestones, and measurable outcomes.
• Build and run operating mechanisms for program health, dependency management, decision-making, and executive visibility across audits, remediation efforts, and control maturity initiatives.
• Modernize the SOX audit program by transitioning compliance workflows from manual, high-toil evidence collection to AI-driven, automated control monitoring and audit readiness, driving greater efficiency and scalability across the organization.
• Partner with Engineering and Product as core strategic partners, and work closely with Finance, engineering control owners, and Contractors to align on priorities, sequencing, ownership, and delivery accountability.
• Drive durable improvements in how the org plans, tracks, and evidences control execution, reducing manual effort and improving consistency, readiness, and trust.
• Anticipate program and technical risks early, frame trade-offs clearly, and influence leaders through crisp recommendations that balance compliance requirements with engineering pragmatism.
• Create best practices, tools, and methodologies that raise execution quality for the broader organization, not just for a single program.
• Use GenAI as the default operating model for EP PgM execution—producing AI-assisted first drafts of core program artifacts, modernizing high-toil workflows into AI-first mechanisms (e.g., intake triage, status synthesis, action/decision extraction, risk & dependency tracking), and synthesizing signals to proactively surface risks, decision/trade-offs, and escalation paths.
• Prototype solutions to augment decisions through data (e.g. dashboards, data analysis) or simplify processes (e.g. process and workflow helpers, or internal tools) using AI coding assistants (“vibe coding”).
• Follow Pinterest AI guidance for risk, governance, and safety-by-design: appropriately handle sensitive data, validate AI-generated outputs, document assumptions/limits, and ensure AI-assisted workflows meet applicable policy/compliance expectations before broad adoption.

What we’re looking for:

• BS in a technical discipline or equivalent experience (7+ years of technical program management or closely related experience leading large-scale technical programs across multiple teams and stakeholders).
• Expertise in navigating the complexities of SOX compliance across distributed engineering and business organizations, driving audit readiness through rigorous program management, clear executive reporting, and alignment across diverse control owners.
• Experience leading large, cross-functional technical programs with significant ambiguity, senior stakeholder management needs, and outcomes that matter at company level.
• Demonstrated ability to influence Engineering, Product, Finance, and other strategic partners through strong judgment, structured execution, and clear communication.
• Strong program leadership in environments with complex dependencies, shifting priorities, risk management needs, and a mix of technical and business stakeholders.
• Comfort operating deeply in engineering contexts: understanding system constraints, challenging assumptions, surfacing technical risks, and helping teams make sound trade-offs.
• Track record of building mechanisms that scale—operating rhythms, governance, templates, tools, and processes that improve quality and predictability across many teams.
• Domain strength in compliance, controls, audit readiness, or similarly regulated/risk-sensitive environments is strongly preferred.
• AI-first execution mindset: demonstrated ability to use GenAI to accelerate planning, program operations, and stakeholder communications—starting with AI drafts and applying strong judgment to validate, refine, and drive decisions.
• Workflow design, AI fluency, data & insights orientation: experience turning repeatable program work into durable, low-toil mechanisms and improving decision-making by using GenAI (e.g., strong prompting, vibe coding lightweight scripts/tools, dashboards, data analysis and leveraging agents where appropriate)
• Safety-by-design AI fluency: experience operating within AI governance expectations (risk assessment, data handling, model/output validation, auditability/traceability) and proactively identifying where AI use is not appropriate or requires additional controls.